code: def __init__(self):
      super(Net, self).__init__()
      self.conv1 = nn.Conv2d(1, 20, 5, 1)
      self.conv2 = nn.Conv2d(20, 50, 5, 1)
      self.fc1 = nn.Linear(4 * 4 * 50, 500)
      self.fc2 = nn.Linear(500, 10)
  
file_path: analytics-zoo/pyzoo/zoo/examples/pytorch/train/mnist/main.py
imports: from __future__ import print_function
  import argparse
  import torch
  import torch.nn
  import torch.nn.functional
  from torchvision import datasets, transforms
  from zoo.pipeline.api.torch import TorchModel, TorchLoss, TorchOptim
  from zoo.pipeline.estimator import *
  from bigdl.optim.optimizer import SGD, Adam
  from zoo.common.nncontext import *
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.metrics import Accuracy
  from zoo.util.utils import detect_conda_env_name
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net()